Genetic diversity and differentiation of populations of Anthyllis vulneraria along elevational and latitudinal gradients

Abstract The abundant centre model (ACM) predicts that the suitability of environmental conditions for a species decreases from the centre of its distribution toward its range periphery and, consequently, its populations will become scarcer, smaller and more isolated, resulting in lower genetic diversity and increased differentiation. However, little is known about whether genetic diversity shows similar patterns along elevational and latitudinal gradients with similar changes in important environmental conditions. Using microsatellite markers, we studied the genetic diversity and structure of 20 populations each of Anthyllis vulneraria along elevational gradients in the Alps from the valleys to the elevational limit (2500 m) and along a latitudinal gradient (2500 km) from Central Europe to the range margin in northern Scandinavia. Both types of gradients corresponded to an 11.5°C difference in mean annual temperature. Genetic diversity strongly declined and differentiation increased with latitude in line with the predictions of the ACM. However, as population size did not decline with latitude and genetic diversity was not related to population size in A. vulneraria, this pattern is not likely to be due to less favorable conditions in the North, but due to serial founder effects during the post‐glacial recolonization process. Genetic diversity was not related to elevation, but we found significant isolation by distance along both gradients, although the elevational gradient was shorter by orders of magnitude. Subarctic populations differed genetically from alpine populations indicating that the northern populations did not originate from high elevational Alpine ones. Our results support the notion that postglacial latitudinal colonization over large distances resulted in a larger loss of genetic diversity than elevational range shifts. The lack of genetic diversity in subarctic populations may threaten their long‐term persistence in the face of climate change, whereas alpine populations could benefit from gene flow from low‐elevation populations.


| INTRODUC TI ON
The genetic diversity of populations and their differentiation is influenced both by contemporary evolutionary processes like gene flow, genetic drift, and natural selection and by the history of a species (Frankham et al., 2017). In small and isolated populations genetic variation is often strongly reduced and genetic divergence among populations increased because of reduced gene flow and stronger genetic drift (Aguilar et al., 2008;Fischer & Matthies, 1998;Schlaepfer et al., 2018). Bottlenecks and founder effects may also have strong negative effects on genetic diversity (Frankham et al., 2017). Due to environmental gradients, the processes that influence genetic diversity often vary across the distributional range of a species. The abundant centre model (ACM) predicts that the suitability of environmental conditions for a species decreases from the centre of its distribution to its range periphery and consequently its populations will become scarcer, smaller and more isolated toward the range limits (Brown, 1984;Sagarin & Gaines, 2002). Genetic consequences of the decrease in the number and size of populations toward the range periphery and their increasing isolation are predicted to be reduced genetic diversity within populations and increased genetic differentiation among populations due to increased genetic drift and reduced gene flow at the periphery of the distribution of a species Hardie & Hutchings, 2010;López-Delgado & Meirmans, 2022;Sexton et al., 2009). However, while a recent review found that only approximately half of the available studies supported these predictions (Pironon et al., 2017), a study of 91 North American native plants found strong support for the ACM (López-Delgado & Meirmans, 2022).
The genetic diversity and population structure of plant species across its range may also be influenced by range shifts linked to Pleistocene climate oscillations (Harter et al., 2015), which had a major impact on the present distribution of plants (Hewitt, 2000).
Populations typically retained high levels of genetic diversity and allelic richness in the glacial refugia where they survived during the ice ages (Beatty & Provan, 2011;López-Delgado & Meirmans, 2022).
With the retreat of the ice shields after climate warming, individuals from the surviving populations colonized the new suitable habitats.
Postglacial colonization over long distances by serial founder events often resulted in a decline in genetic diversity. Thus, populations often have less genetic variation at higher latitudes and are genetically more differentiated than at lower latitudes (Ehrich et al., 2007;Hewitt, 2004;López-Delgado & Meirmans, 2022). However, northern populations in Europe may also have become established by a massive migration of cold-tolerant plants from the Central European tundra into the forelands of retreating ice shields during the window of opportunity before tree species migrated North. In this scenario one would expect that genetic diversity within populations would not decrease toward the northern periphery. An example is the artic-alpine species Dryas octapetala whose genetic diversity in Scandinavian populations is high and today's arctic populations of the European cluster are closely related to alpine populations indicating a common origin in the tundra south of the Scandinavian ice-shield (Skrede et al., 2006). Important environmental conditions (e.g. temperature) that influence the suitability of habitats for a species may change along elevational gradients in similar ways as with latitude and influence the balance between drift and gene flow. However, there are also important differences between the changes in environmental conditions along the two types of gradients, including those in day length, irradiance, CO 2 partial pressure, and precipitation (Körner, 2007).
Moreover, elevational gradients are much shorter than latitudinal ones, and thus gene flow between populations is more likely (Hahn et al., 2012;Halbritter et al., 2015). Four patterns of genetic diversity along elevational gradients have been found (Itino & Hirao, 2016;Ohsawa & Ide, 2008): (1)  elevations are optimal, whereas populations at the lower and upper elevation edges are more affected by restricted gene flow, genetic drift and founder effects, leading to reduced genetic diversity (Byars et al., 2009;Herrera & Bazaga, 2008;Meng et al., 2019;Ohsawa et al., 2007). (2) Populations at low elevations are genetically most diverse (Premoli, 2003;Quiroga & Premoli, 2007) because conditions at low elevations are best and founder effects have occurred during upward range expansion. (3) Genetic diversity increases with elevation in species whose main habitats are in the alpine zone, or whose populations are negatively impacted by human activities at lower elevations (e.g. Halbritter et al., 2015;Reisch et al., 2005;Shi et al., 2011). Finally, genetic diversity may be unrelated to elevation due to extensive gene flow or random variation caused by strong local factors (Hahn et al., 2012;Halbritter et al., 2015). Reviews of studies on genetic diversity along elevational gradients have found no general patterns (Itino & Hirao, 2016;Ohsawa & Ide, 2008), and little is known about whether latitudinal and elevational gradients in environmental conditions have similar effects on the genetic structure and diversity of a plant species. A better understanding of patterns of genetic diversity and differentiation along these gradients is important because genetic diversity will determine the potential of populations to adapt to ongoing global change (Jump et al., 2009).
The effects of the two types of gradients should ideally be compared in species that have both a large latitudinal and elevation extension (Halbritter et al., 2015). We chose the kidney vetch Anthyllis vulneraria (Fabaceae) as a model species to study the patterns of genetic variability and differentiation as influenced by latitude and elevation because it has an exceptionally wide geographic and elevational distribution in Europe. The large distribution of A. vulneraria allowed us to study general genetic patterns that cannot be detected in arctic-alpine species or in rare species with fragmented and isolated populations. We studied the genetic diversity and structure of A. vulneraria along two gradients chosen to correspond to a change of 11.5°C in annual mean temperature: a latitudinal gradient of c. 2400 km from Central Europe to Iceland and northern Norway and three elevational gradients of c. 2000 m elevational difference in the European Alps (see also Daco et al., 2021). The latitudinal gradient ranged from the centre of the distribution of A. vulneraria to its northern range limit and the elevational gradient in the Alps from the valleys to the upper elevational edge of its distribution. We address the following specific questions: (1) Does the genetic diversity of A. vulneraria vary similarly along gradients of elevation and latitude? (2) Are patterns of genetic differentiation similar along the two types of gradients? 2 | MATERIAL S AND ME THODS

| Study species
Anthyllis vulneraria L. (Fabaceae) is a diploid biennial to perennial herb of nutrient-poor calcareous grasslands and screes. Its distribution is exceptionally wide as it occurs from the North of the African continent across Europe to above 70°N in Scandinavia and from sea level up to 3000 m a.s.l. (Conert, 1975). A. vulneraria is not threatened in most parts of its distribution area but has become less common in certain geographical areas (e.g. Jansen et al., 2019). The flowers of A. vulneraria are grouped in heads and seed mass varies between 1.9 and 4.0 mg across the studied distribution range (Daco et al., 2021).
A. vulneraria has been found to be auto-or xenogamous in different populations (Couderc, 1971;Navarro, 1999). Several subspecies of A. vulneraria have been described as the species is very polymorphic (Cullen, 1968), but molecular genetic studies did not support the splitting into numerous subspecies (Köster et al., 2008;Nanni et al., 2004). In the present study, we did not differentiate between infraspecific taxa because we wanted to capture a large amount of genetic variation.

| Sampling
We sampled 20 populations each of A. vulneraria along elevational and latitudinal gradients ( Table 1)
To estimate the error rate, we extracted and genotyped 5% of the samples twice. The mean error rate per sample was calculated as the number of errors divided by the total number of analyzed loci within replicated samples. We randomly chose one of the repeated samples to continue with the analyses.

| Analysis of genetic diversity
All analyses unless otherwise stated were carried out using IBM SPSS Statistics for Windows, version 25.0 (IBM Corp.). Genetic diversity indices including number of multi-locus genotypes (N G ), number of private alleles (N P ), number of alleles (N A ), number of effective alleles (N E ), and observed and unbiased expected heterozygosity (H O and uH E , respectively) were estimated in GenAlEx 6.5 (Peakall & Smouse, 2006, 2012. Allelic richness (A R ) was calculated with the R-package PopGenKit 1.0 (Rioux Paquette, 2012) and the inbreeding coefficient (F IS , Weir & Cockerham, 1984) was calculated in FSTAT 2.9.4 (Goudet, 2003). We used regression analysis to test for the effects of elevation and latitude on diversity measures and to test for the effect of population size on uH E and F IS . Population size was logtransformed prior to analysis.
We tested for the significance of heterozygote deficiency or excess (Hardy-Weinberg equilibrium)

| Analysis of population differentiation
We used F ST (Weir & Cockerham, 1984) and

TA B L E 1 (Continued)
and both geographical distances and the differences in elevation with a linear model. p-values were derived from sequential permutation tests with 1000 permutations using lmPerm. We also tested whether the mean genetic distance between pairs of populations differed between populations north of 56°N and those further south by relating the genetic distances to the geographic distances and population type using a permutational analysis of covariance with 1000 permutations using lmPerm.

| Analysis of population genetic structure
We conducted a principal coordinate analysis (PCoA) based on pairwise G" ST -values between populations. We fitted the two variables elevation and latitude on the ordination using the envfit function in the R-package vegan 2.5-7 (Oksanen et al., 2020).
We used STRUCTURE 2.3.4 (Pritchard et al., 2000) to analyze the genetic structure of the 40 A. vulneraria populations. To estimate the number of genetic clusters (K), we carried out ten independent runs with K = 1-20 with 10 6 Markov chain Monte Carlo (MCMC) iterations after a burn-in period of 10 5 , using the model with correlated allele frequencies and assuming admixture. We decided on the most probable number of K based on the log probability of the data and their variability associated with each K (Gilbert et al., 2012;Pritchard et al., 2007) and the consistency with the PCoA. We used CLUMPAK (Kopelman et al., 2015) to summarize the runs and generate bar plots of cluster assignments.

| Spatial genetic structure within populations
We carried out a spatial autocorrelation analysis with SPAGeDi 1.5d (Hardy & Vekemans, 2002) using the kinship coefficient F ij (Loiselle et al., 1995)

| Population genetic structure
The first two axes of the PCoA explained 35.6% of the variation In the STRUCTURE analysis, the log probability of the data [ln P(D)] increased gradually and the value that also converged well across the 10 independent runs was obtained for K = 7 ( Figure S1). However, the patterns for K = 6 and 7 were very similar, and we therefore preferred the lower number of groups. Structuring the populations into six clusters grouped the 10 most northern populations together (Figure 4a
only a small proportion (4.8%) of the genetic variation was among the three mountain regions, the differentiation among populations within regions was much higher (15%). Most of the genetic variance was within populations (Table 2).
Pairwise population F ST and G" ST -values between all populations are given in Table S1.  Table 1.  Genetic and geographical distances of the populations in the Alps were also related ( Figure 7b, b = 0.0008, p < .001). Moreover, adjusted for the effects of geographical distance, genetic differentiation between the populations in the Alps also increased with their difference in elevation (Figure 7c, b = 0.129, p = .013). The effects of 1 km difference in elevation on the genetic distance between populations were similar to those of a difference of 161.3 km in horizontal distance indicating that the effects of vertical were much stronger than those of horizontal distance. However, the maximum elevational distance between populations was only 2 km.

| Spatial genetic structure within populations
Spatial autocorrelation analysis within populations showed that mean kinship coefficients decreased with distance between plants in the populations (b = −0.00044, p < .001; Figure 8). Plants growing less than 2 m from each other had a higher probability to be genetically related than plants separated by greater distances, suggesting limited gene flow due to restricted pollinator movement and limited seed dispersal.

| DISCUSS ION
Our results show that the patterns of genetic diversity and differentiation of the populations of the widespread plant species Anthyllis vulneraria differ between the elevational and latitudinal gradients.

F I G U R E 6
The relationship between the mean genetic distance (G" ST ) of each population to all others and its genetic diversity (uH E ) for populations along the elevational and latitudinal gradient. found in many species (Gougherty et al., 2020;Hirao et al., 2017;Hirsch et al., 2015; but see Casazza et al., 2021;Ilves et al., 2016;Plenk et al., 2017). However, the ACM assumes that the lower genetic diversity and stronger differentiation among peripheral populations is due to less favorable conditions, which lead to smaller and more isolated populations and subsequently to genetic erosion and strong differentiation Hardie & Hutchings, 2010;Sexton et al., 2009). In contrast, in A. vulneraria the size of populations increased with latitude indicating favorable conditions in the north (Daco et al., 2021), and genetic variation was not related to current population size. This suggest that not current conditions resulting in fragmentation, but historical processes (colonization after the ice age) are responsible for the much lower genetic diversity of northern populations. Other short-lived plant species like Arabidopsis thaliana (Lewandowska-Sabat et al., 2010) or Plantago coronopus (Berjano et al., 2015), which have migrated north after the retreat of the ice sheet after the Last Glacial Maximum also showed such genetic patterns. A similar combination of founder effects followed by demographic expansion as in A. vulneraria has been suggested as the reason for the population structure of Scandinavian Trollius europaeus (Despres et al., 2002).
The decline of genetic diversity with increasing latitude was essentially restricted to populations situated north of 56°N latitude (pop. no. 10 to 20). This limit corresponds to the southern limit of the ice-shield during the Younger Dryas period (Stroeven et al., 2016).
Populations north of this latitude also formed a distinct cluster in the STRUCTURE and PCoA analyses. The decrease of genetic diversity and the increasing differentiation with latitude suggests that northern populations lost genetic diversity due to serial founder effects during the colonization of northern Europe after the ice age, producing genetically isolated populations with very low subsequent gene flow among them (Despres et al., 2002;Excoffier et al., 2009). The rare presence of the Scandinavian cluster in lowland populations in Central Europe are in line with the hypothesis that the Scandinavian populations were founded by random individuals from lowland Central European populations that migrated north after the retreat of the ice sheets. In contrast, our results do not support for A. vulneraria the scenario that arctic populations of species that also occur in the Alps were founded by alpine genotypes (Albach et al., 2006;Despres et al., 2002;Ehrich et al., 2007;Schönswetter et al., 2003;Skrede et al., 2006), as no high-elevation genotypes of the Alps were found in the Scandinavian populations of A. vulneraria. In contrast to studies that compared populations of arctic-alpine species, we were able to detect the importance of the serial founder effects during recolonization after the ice-age in in glacier forelands when the ice shields retreated due to the short geographical distances from lowland to alpine environments. The alpine environment was to those cold-tolerant genotypes not ecologically marginal as predicted by the ACM but, in fact, corresponded largely to their ecological niche in the tundra of the lowlands. A third possible explanation would be that cold-tolerant plants survived locally in nunataks (see Schneeweiss & Schoenswetter, 2011) and colonized in post-glacial times glacier forelands and alpine meadows.
However, in this case we would expect strong genetic differentiation among mountain regions and reduced genetic diversity in high elevation populations due to long-term isolation and low population sizes of the source populations in the isolated nunataks (Stehlik et al., 2002). Our results are not in line with the nunatak hypothesis as genetic differentiation among mountain regions was rather low and genetic diversity did not decrease with altitude.
Along both gradients, we found significant isolation by distance patterns, indicating that gene flow is restricted and strongest between geographically close populations. However, a vertical (elevational) distance of a certain length between populations in the Alps resulted in a much stronger genetic differentiation between populations than the same horizontal distance between populations of the latitudinal gradient. This could be due to phenological differences in flowering periods that may restrict cross-fertilization among populations at different elevations (Premoli, 2003;Reisch et al., 2005;Yamagishi et al., 2005). However, overall the genetic differentiation between valley and alpine populations of A. vulneraria was much smaller than between Central European and subarctic populations along the same gradient in mean annual temperature (11.5°C) because the elevational gradients were much shorter than the latitudinal gradient. The kinship analysis revealed that gene flow is even restricted over short distances within populations, which may be due to restricted pollinator movement and seed dispersal.
Peripheral populations of A. vulneraria in northern Europe separated by a certain spatial distance were more differentiated genetically than populations in Central Europe, indicating lower gene flow between them. A possible reason are greater mean spatial distances between neighboring populations in the North. Occurrence data from GBIF.org (2022) appear to support this, but might not be representative. A decline of population frequency toward the range periphery would be in line with the predictions of the ACM. The recent review of studies testing the ACM (Pironon et al., 2017) found that while there was only limited support for a general decline in population size, there was much stronger support for the prediction that the frequency of populations declines toward the range periphery.

| CON CLUS IONS
Populations along the two gradients showed very different patterns of genetic diversity and genetic differentiation. While A. vulneraria maintained high amounts of genetic diversity in its Alpine and Central European populations, toward the North genetic diversity decreased strongly and genetic differentiation among populations increased due to serial founder effects during post-glacial recolonization. Our results support the notion that postglacial latitudinal colonization over large distances results in a larger loss of genetic diversity than elevational range shifts (Ehrich et al., 2007;Hewitt, 1999). Subarctic populations differed genetically from alpine populations, indicating that the subarctic populations did not originate from the high elevational alpine ones.
The consistently high genetic diversity, allelic richness and num-

CO N FLI C T O F I NTE R E S T
The authors declare that they have no conflict of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
Individual genotype data are available at Dryad https://doi. org/10.5061/dryad.ht76h drjp.